Neurons are specialized cells that transmit information through electrical and chemical signals using structural processes known as dendrites and axons. Dendrites receive information for the cell to interpret while the exceedingly long axon transmits the processed information to its target destination. To ensure the neuron properly carries out its extracellular functions, the orchestration of intracellular cargo (e.g. mitochondria) is critical. This is especially true in the axon, which can be up to a meter in length. There are many challenges involved in the spatial and temporal regulation of cargo over such vast cellular distances. In order to accomplish cargo transport between the cell body and axon terminus the neuron has developed an efficient process to overcome this challenge called axonal transport. Axonal transport utilizes a system of molecular motors coupled to cargo, creating a multi-motor complex, which walks along a set of tracks to position the cargo at the right time and place. One class of molecular motors, called kinesin, are used to traffic cargo away from the cell body and walk along microtubule tracks. These motors work in teams to navigate a complex microtubule landscape that is rich in microtubule-associated proteins (MAPs). One MAP abundantly found within the axon is called Tau and is implicated in a variety of neurodegenerative disorders (e.g. Alzheimer's disease). Much attention has been focused on the kinesin-1 motor while investigating the axonal transport process. However, kinesin-2 plays an equally important role and is not as well characterized as kinesin-1. Previously, it has been demonstrated, in vitro, that Tau disrupts kinesin-1 transport, even below physiological concentrations, however, in vivo evidence suggests the contrary. Given this discrepancy, there are likely other cellular systems in place to provide the necessary navigation of Tau obstacles. One solution may involve multi-motor complexes using two kinesin family members attached to cargo, as both kinesin-1 and kinesin-2 have been observed coupled to cargo. In order to peel away the complex layers of kinesin-1 and kinesin-2 coupled cargo inside the axon, single-molecule imaging techniques were employed to observe the individual behavior of both kinesin-1 and kinesin-2, in vitro. Further, using a combination of genetic engineering, single-molecule analysis and mathematical modeling has helped elucidate differences between these two motors. Kinesin-2 was found to be insensitive to Tau obstacles, unlike kinesin-1, which is in part due to a longer region of the motor called the neck-linker. This region connects the motor domain, which interfaces with the microtubule track, to the coiled-coil stock, which interfaces with the cargo. When the neck-linker lengths were swapped between the motors their behavior in the presence of Tau also switched, and kinesin-2 became sensitive to Tau. To understand kinesin-2's mechanism of navigating Tau obstacles, we looked at the lateral stepping characteristics of both motors. We observed kinesin-2's lateral stepping frequency to be 2-4 fold higher than kinesin-1 and independent of the microtubule obstacle concentration. Thus, kinein-2's longer neck-linker allows a more agile walk along the microtubule surface to navigate obstacles more efficiently than kinesin-1. In a multi-motor complex containing both motors, kinesin-2 is more efficient at maneuvering around MAPs while kinesin-1, which has previously been demonstrated to sustain a higher stall force, is more efficient at towing cargo. This work demonstrates how teams of directionally similar motors may work together to position cargo during axonal transport.

<p> Advances in electron microscopy (EM) allow for structure determination of large macromolecular machines at increasingly high resolutions. A key step in this process is interpreting the EM density map with structural models of maximal accuracy and optimal precision. Model precision should be determined by the uncertainty in the experimental data; however, current methods only set uncertainty in an <i>ad hoc</i> manner with arbitrary weight terms. Thus, there is a need for more objective methods.</p><p> In Chapter 2, I present a novel Bayesian approach to modeling macromolecular structures based on EM density maps. The key advancement is the development of a scoring function that uses the local uncertainty of the density map to set the data weight and allows for correlation between neighboring density values. Unlike traditional approaches, the score does not require an expert user to set arbitrary parameters. I assessed the accuracy of models generated by this approach with a set of experimentally-derived, previously-published EM data of macromolecular complexes at varying resolutions from 3 to 6&Aring;. I found that this approach leads to higher fluctuations in the model ensemble in locations with higher local uncertainty, and obtained accurate ensembles for a 3.2&Aring; resolution map of Trpvl and 3.4&Aring; and 5.4&Aring; resolution maps of &gamma;-secretase.</p><p> In Chapter 3, I present models of the &gamma;-tubulin small complex in two functional states based on a challenging data set consisting of low-resolution EM density maps and a remotely related structure. Here, I used a traditional scoring techniques, but extensively sampled alignments and conformations in order to ensure that the model ensemble reflected the uncertainty in the data. The resulting models form a tight cluster for each state and were consistent with a set of newly reported chemical cross-links. Comparing the two states, I found significant structural differences and predict stabilizing interactions of the two states. The work in this chapter shows the difficulties of traditional modeling and serves as motivation for the methods developed in Chapter 2. </p><p> Both approaches are incorporated into the open source <i>Integrative Modeling Platform</i> (IMP) package, enabling integration with multiple other data types and usage of myriad sampling and analysis tools. </p>

<p>Many microbial pathogens deliver effector proteins, via type III secretion system, into infected host cells. Elucidating the function of these effectors is essential for our understanding of pathogenesis. Here I describe biochemical and structural characterization of an effector protein (NleL) from E. coli O157:H7, a widespread pathogen causing severe food borne diseases. NleL functionally and structurally mimics eukaryotic HECT E3 ligases and catalyzes formation of unanchored polyubiquitin chains using K6 and K48 linkage. The catalytic cysteine residue forms a thioester intermediate with ubiquitin. The structure of NleL contains two domains, a &#946;-helix domain formed by pentapeptide repeats and a bilobed catalytic domain reminiscent of the N- and C-lobe architecture of HECT E3sstructures of NleL observed in two crystal forms revealed a large range of different positions of the C-lobe relative to the N-lobe, indicating that the helix linking the two lobes is extremely flexible. Comparing the structure of NleL with that of the Salmonella homolog SopA showed that the orientation of the C-lobes differ by as much as 108?, suggesting that large movements of the C-lobe may be required to facilitate the transfer of ubiquitin from E2 to the substrate. In the structure of NleL/UbcH7 complex, UbcH7 binds at the end of the N-lobe that is closer to the C-lobe as observed in the structure of SopA/UbcH7 complex. The conserved phenylalanine of E2s (Phe63 of UbcH7) is involved heavily in the binding. The C-lobe of NleL in the complex rotates as much as ~168? towards UbcH7 compared with the structures of the isolated NleLs and the catalytic cysteines of E2 and E3 are within 7? of each other. In the structure of SopA/UbcH7 complex, the C-lobe bends towards the putative substrate binding domain (&#946;-helix domain). The orientation of the C-lobes in the NleL and SopA complexes differs by ~180?, demonstrating that large movements of the C-lobes are possible, and the two complexes could represent two different stages of the transfer of ubiquitin from E2 to the substrate. These results provide critical knowledge towards understanding the molecular mechanism by which pathogens utilize the host ubiquitination system during infection.

The success of protein structure modeling by homology requires an accurate sequence alignment between the query sequence and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that would produce the best structural model is generally not optimal, in the sense of having the highest DP score. Suboptimal alignment methods can be used to generate alternative alignments, but encounter difficulties given the enormous number of alignments that need to be considered. We present here a new suboptimal alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements (SSEs) and combining high-scoring fragments that pass basic tests for 'modelability', we can generate accurate alignments within a set of limited size. Chapter 1 introduces the field of protein structure prediction in general and the technique of homology modeling in particular. One subproblem of homology modeling -- the sequence to structure alignment of proteins -- is discussed in Chapter 2. Particular attention is given to descriptions of the size, density and redundancy of alignment space as well as an explanation of the dynamic programming technique and its strengths and weaknesses. The rationale for developing alternative alignment techniques and the unique difficulties of these methods are also discussed. Chapter 3 explains the methodologies of S4 -- the alternative alignment program we developed that is the main focus of this thesis. The process of finding alternative alignments with S4 involves several steps, but can be roughly divided into two main parts. First, the program looks for combinations of high-similarity fragments that pass basic rules for modelability. These 'fragment alignments' define regions of alignment space that can be searched more thoroughly with a statistical potential for a single representative for that region. The ensemble of alignments that is thus created needs to be evaluated for accuracy against the correct alignment. Current methods for doing so, as well as adjustments to those methods to better suit the realm of remote homology alignments, are discussed in Chapter 4. A novel measure for determining similarity between alignments, termed the inter-alignment distance (IAD) also is developed. This measure can be used to assess quality, but is also well-suited to finding redundant alignments within an ensemble. In Chapter 5, the results of testing S4 on a large set of targets from previous CASP experiments are analyzed. Comparisons to the optimal alignment as well as two standard alternative alignment methods, all of which use the same similarity score as S4, demonstrate that S4's improvement in accuracy is due to better sampling and filtering rather than more sophisticated scoring. Models made from S4 alignments are also shown to significantly improve upon those made from optimal alignments, especially for remote homologs. Finally, an example of a sequence to structure alignment offers an in depth explanation of how S4 finds correct alignments where the other methods do not. Chapter 6 describes a set of three experiments that paired S4 with the model evaluation tool ProsaII in a homology modeling pipeline. There were two primary objectives in this project. First, we wanted to test different methods for finding remote homologs that could serve as input to S4. And second, we evaluated the use of ProsaII as a method for discriminating between good and bad models, and thus also between homologous and non-homologous templates. The first two experiments are essentially blind searches for homologous sequences and structures. The third experiment takes remote templates returned by PSI-BLAST and uses S4 and ProsaII to find alignments and determine whether the template is a structural homolog. While S4 was able to find homologs in the blind searches, the alignment/model quality and level of discrimination was found to be higher when the input to the pipeline came from a set of structures produced by a template selection method. Finally, Chapter 7 discusses the consequences of this research and suggests future directions for its application.

Voltage-gated ion channels make up a superfamily of membrane proteins involved in selectively or non-selectively conducting charged ions, which can carry current in and out of cells, in response to changes in membrane voltage. Currents carried by ion channels influence the voltage across the cell membrane, which can trigger changes in the conductance of neighboring voltage-gated channels. In this way, signals, measured as transient changes in voltage called action potentials, can be sent through and between cells in order to transmit information quickly and efficiently throughout excitable systems. My thesis work focuses on elucidating the mechanisms underlying the voltage-dependent gating of a member of the voltage gated potassium (Kv) channel family, KCNQ1 (Kv7.1). Like other members of the voltage gated potassium family, the KCNQ1 channel is made up of four subunits, each containing a voltage sensing domain and a pore-forming domain. Tetrameric channels form with a single central pore domain, and four structurally independent voltage sensing domains. KCNQ1 plays roles both in maintenance of the membrane potential (it forms a leak current in epithelial cells throughout the body) as well as a very important role in resting membrane potential reestablishment (it forms a slowly activating current important in action potential repolarization in cardiac cells). In order to serve these varied functions, KCNQ1 displays uniquely flexible gating properties among Kv channels. Evidence of this flexibility is found in the observation that the presence or absence of various beta subunits can cause the channel to be non-conducting, slowly activating with a large conductance, quickly activating with a small conductance, or constitutively active. My thesis project has been to unravel the mechanisms underlying these very different phenotypes, focusing on the role of the voltage sensor and its coupling to the channel gate. Most of this work focuses on the role of KCNQ1 in the heart, where it comprises the alpha subunit of the slowly activating delayed rectifier current, IKs. This current plays a major role in repolarization of the cardiac action potential, evidenced in part by its major role in shortening the action potential in the face sympathetic stimulation, which leads to phosphorylation-induced increase in IKs current. Further evidence for the importance of IKs to proper cardiac function is found through the identification of many mutations to IKs that result in cardiac arrhythmia, most notably Long QT syndrome, which results from loss of IKs current and an associated prolongation of the cardiac action potential. In addition, gain-of-function IKs mutations have been implicated in Short QT Syndrome and an inherited form of atrial fibrillation. In order to understand mechanisms underlying the physiological and pathophysiological functions of IKs, a more complete picture of its structure and function are needed. One major goal in the pursuit of a more complete characterization of IKs is to understand the interaction between the IKs alpha subunit, KCNQ1 and its modulatory subunit KCNE1, which has been shown to profoundly affect the gating of the KCNQ1 channel. Among the effects of KCNE1 co-expression are a slowing of channel activation, a slowing of deactivation, a depolarizing shift in the voltage dependence over which the channel activates and an increase in conductance through the KCNQ1 channel pore. To this point, a complete structural and functional basis for these myriad biophysical alterations has not been established. In order to better understand the gating of KCNQ1, this work develops a voltage sensor assay, voltage clamp fluorometry, to measure movements of the voltage sensor and explore changes to the voltage sensor induced by KCNE1 and disease-causing mutations. Chapter 1 validates this technique using mutagenesis to ensure the assay reports on voltage sensor movement. A preliminary characterization of voltage-dependent gating in homomeric KCNQ1 channels reveals an unexpected relationship between voltage sensor movement and channel opening. Chapter 1 then looks at the effect of KCNE1 on voltage sensor movement and coupling to the channel gate, finding both to be significantly altered in the presence of this beta subunit. Returning to the homomeric KCNQ1 channel, Chapter 2 further probes its gating and develops a model based on the prediction that KCNQ1 voltage sensors act as allosteric regulators of the channel gate. This scheme can make predictions about what gating processes are affected by permutations such as KCNE1 co-expression and the presence of disease-associated mutations. Finally, Chapter 3 explores the effects of two atrial fibrillation associated mutations on KCNQ1 gating using electrophysiology, biochemistry, and VCF. Through these results, this work provides novel insight into structures and interactions that are important for gating in both physiological and pathophysiological states.

The dynamics of proteins on the millisecond time scale are on the same time scale as typical catalytic turnover rates, and can sometimes be closely related to enzymes' functions. Solid state NMR, equipped with magic angle spinning, is a very good technique to detect such millisecond dynamics, because it is suitable for many protein systems such as membrane proteins, and the anisotropic interactions recoupled in the solid state NMR can supply valuable geometric information regarding the dynamics. In this thesis, I mainly focus on the developing new dynamics detection pulse sequences based on previous Centerband-Only Detection of Exchange (CODEX) experiment and applying CODEX experiments to an enzyme system, triosephosphate isomerase (TIM), for studying the function of the millisecond dynamics in catalysis. Two newly developed pulse sequences, Dipolar CODEX and R-CODEX use the 13C-15N (Dipolar CODEX) and 1H-13C or 1H-15N (R-CODEX) dipolar couplings to detect dynamics. Compared with the chemical shift anisotropy used in the CODEX experiment, the dipolar coupling has a more direct relationship with the molecular geometry and could be better for extracting geometric information regarding reorientations. A special characteristic of the R-CODEX sequence is that the use of an R-type dipolar recoupling sequence can suppress the effect of 1H-1H homonuclear couplings. This approach paves the way to detect both the correlation time and reorientational angle of the dynamics in fully protonated samples. These two pulse sequences are tested by detecting the π flip motion of urea and methylsulfone imidazole. The R-CODEX experiment is compared with two other millisecond dynamics detection methods: 2D-exchange experiments and line-shape analysis, using the example of in crystalline L-phenylalanine hydrochloride. The millisecond ring flip motion of the aromatic ring in L-phenylalanine hydrochloride is characterized in detail for the first time. The comparison between these three methods shows that the R-CODEX experiment does not require a chemical shift change in the process of the motion and that it can detect the dynamics even if there is the peak overlap in the spectra. Triosephosphate isomerase (TIM) is a well-known highly efficient enzyme. Its loop motion (loop 6) has been extensively studied and been proven to be correlated with product release and be a rate-limiting step for the catalysis. Another highly conserved loop near the active site, loop 7 also has large changes in dihedral angles during ligand binding. Its motion is suspected to be correlated with loop 6 based on mutant experiments and solution NMR studies. However, the core sequence of loop 7, YGGS, is missing in the solution NMR spectrum. We assigned the GG pair in loop 7 (G209-G210) using 1-13C, 15N glycine labeling and solid state NMR experiments, and detected the loop 7's motion using 1-13C glycine labeling and CODEX experiments. We found that loop 7's motional rate (300+/-100 s-1) at -10oC agrees well with previously detected motional rates of loop 6 extrapolated from higher temperatures using an Arrhenius plot. This suggeststhat the motion of loop 6 probably correlates with loop 7. At the same time, the line-shape analysis for another GG pair (G232-G233), which forms hydrogen bonds with the ligand, indicates a ligand release rate (400+/-100 s-1) similar to loop 7's rate, supporting the hypothesis that the ligand release is also probably correlated with the motion of loop 7 and loop 6.

The work presented in this dissertation focuses on the kinetics of biomolecular reactions under mechanical force, including protein unfolding and disulfide-bond reduction, probed at the single-molecule level. The advent of single-molecule force spectroscopy has allowed the direct measure of force-dependent reaction rates, providing a powerful approach to extract the kinetic information and to characterize the underlying energy landscape that governs the reaction. The widely accepted two-state kinetic model for protein unfolding describes that the protein unfolds by crossing over a single energy barrier, with the implicit assumption of a single transition state and a well-defined activation energy barrier. Based on this assumption, the ensemble-averaged survival probability is expected to follow single exponential time dependence. However, it has become increasingly clear that the saddle point of the free-energy surface in most reactions is populated by ensembles of conformations, leading to nonexponential kinetics. Here we present a theory that generalizes the two-state model to include static disorder of conformational degrees of freedom to fully account for a diverse set of unfolding pathways. Using single-molecule force-clamp spectroscopy, we study the nonexponential kinetics of single ubiquitin proteins unfolding under constant forces. We find that the measured variance in the barrier heights has a quadratic dependence on force. Our study illustrates a novel adaptation of the classical Arrhenius equation that accounts for the microscopic origins of nonexponential kinetics. Our theory provides a direct approach in determining the variance in the barrier heights of a reaction. We extend our theoretical model to investigate the kinetics of two different reactions, protein unfolding and disulfide-bond reduction, both occurring within the same protein molecule. We measure the variance of the barrier heights, which quantifies the heterogeneity of the reaction pathway for both reactions. In contrast to protein unfolding, we find that the variance of the barrier heights for disulfide-bond reduction is close to zero, reflecting the differences between these two reactions. These results strongly suggest that the transition state for a disulfide-bond reduction is well defined, as opposed to protein unfolding. The Bell model assumes that the distance to the transition state is force independent. However, in many systems, it has been observed that the transition state moves toward the destabilized state upon perturbation. This effect, known as the Hammond effect, would predict that the distance to the transition state decreases with force. This hypothesis remains unexplored in protein unfolding under force. To elucidate the conformational plasticity of the transition state structure upon the application of force, we probe the unfolding kinetics of ubiquitin and NuG2 over a broad range of forces. We use the force-ramp assay to measure probability distribution of unfolding forces. Based on the standard two-state model, the force-dependent lifetimes can be obtained by transforming the probability distribution of unfolding forces. However, this formalism is invalid for proteins exhibiting the dispersed kinetics, as we observed in ubiquitin. By measuring the lifetimes over a wide range of forces, we discover that the distance to the transition state for NuG2 exhibits a weak force dependency. The measured value of the distance to the transition state is 0.22 nm, comparable to the size of a water molecule. The observed non-Hammond behavior revealed an integral structural role of water molecules bridging the unfolding transition state, constraining the movement of the unfolding transition state. Finally, in order to test the Kramers theory that would predict that the distance to the transition state continuously decreases with force, we explore the kinetics of disulfide bond reduction by hydroxide anions over a wide range of forces. On the contrary to the Kramers prediction, we observe that the reduction rate exhibits two distinct exponential dependencies on the pulling force, revealing a discontinuous shift in the distance to the transition state. The experimental data show that the distance to the transition state is ~ 0.5 Å in the low-force regime (< 500 pN), and changes to a much shorter value of ~ 0.1 Å in the high-force regime (> 500 pN). We propose a plausible molecular scenario that is consistent with our experimental results. We suggest that the substrate disulfide bond undergoes a conformational change under a stretching force above 500 pN. Our results show the first observation that the application of a mechanical force to the protein disulfide bond causes an abrupt change in reactivity.

Fluorescence microscopy has been a fundamental imaging tool for life science research. Fluorescence basically involves only two molecular states: the ground molecular state and the first singlet excited state (the fluorescent state). Astonishingly, it greatly diversified the applicability of fluorescence microscopy in many different ways by incorporating additional molecular states and switching fluorescent molecules through these three or even more molecular states during the fluorescence process. This switching mechanism between additional molecular states, either long lifetime or short lifetime, and two original molecular states actually adds nonlinearity into the linear fluorescence process, which empowers fluorescence microscopy additional imaging capabilities. Herein, we developed four distinct new imaging techniques by taking advantage of this molecular switching mechanism: dark state dynamics sensing and imaging by fluorescence anomalous phase advance, genetically-encoded microviscosity sensor using protein-flexibility mediated photochromism, deep tissue imaging with super-nonlinear fluorescence microscopy, and light-driven fluorescent timer for simultaneous spatial-temporal mapping of protein dynamics in live cells. The first technique, dark state dynamics sensing and imaging, effectively correlates the first triplet state of fluorescent organic dyes with the fluorescence process to produce fluorescence emission with unexpected phase advance compared with the excitation light, that reflects the real-time information of organic dyes' dark states. The last three techniques all harness the unique on-off switch capability of the optical highlighter fluorescent proteins: Dronpa, a photo-switchable fluorescent protein, is demonstrated to experience medium friction during the chromophore's cis-trans isomerization process while photo-switching from the bright state to the dark state; multiphoton fluorescence microscope could achieve higher order nonlinearity and thus deeper image depth in the scattering sample by the population transfer kinetics of the photoinduced molecular switches, such as photo-activatable fluorescent protein etc.; a photo-convertible fluorescent protein, mEos2, shows slow color conversion from green to red under extremely weak near-UV light, that could be used to time protein age. No matter fluorescent organic dyes or optical highlighter fluorescent proteins, the nonlinearity has been demonstrated to create new fluorescence imaging techniques by switching fluorescent molecules between additional molecular states and two original molecular states involved in the fluorescence process.

abstract: Bio-molecules and proteins are building blocks of life as is known, and understanding their dynamics and functions are necessary to better understand life and improve its quality. While ergodicity and fluctuation dissipation theorem (FDT) are fundamental and crucial concepts regarding study of dynamics of systems in equilibrium, biological function is not possible in equilibrium. In this work, dynamical and orientational structural crossovers in low-temperature glycerol are investigated. A sudden and notable increase in the orientational Kirk- wood factor and the dielectric constant is observed, which appears in the same range of temperatures that dynamic crossover of translational and rotational dynamics oc- cur. Theory and electrochemistry of cytochrome c is also investigated. The seeming discrepancy in reorganization energies of protein electron transfer produced by atom- istic simulations and those reported by protein electrochemistry (which are smaller) is resolved. It is proposed in this thesis that ergodicity breaking results in an effective reorganization energy (0.57 eV) consistent with experiment. Ergodicity breaking also affects the iron displacement in heme proteins. A model for dynamical transition of atomic displacements in proteins is provided. Different temperatures for rotational and translational crossovers of water molecules are re- ported, which all are ergodicity breaking transitions depending on the corresponding observation windows. The comparison with Mössbauer spectroscopy is presented. Biological function at low temperatures and its termination is also investigated in this research. Here, it is proposed that ergodicity breaking gives rise to the violation of the FDT, and this violation is maintained in the entire range of physiological temperatures for cytochrome c. Below the crossover temperature, the protein returns to the FDT, which leads to a sudden jump in the activation barrier for electron itransfer. Finally the interaction of charges in dielectric materials is discussed. It is shown that the potential of mean force between ions in polar liquids becomes oscillatory at short distances. / Dissertation/Thesis / Doctoral Dissertation Physics 2018

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